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Multiwindow estimators of correlation

dc.contributor.authorScharf, Louis L., author
dc.contributor.authorMcWhorter, L. Todd, author
dc.contributor.authorIEEE, publisher
dc.date.accessioned2007-01-03T04:21:02Z
dc.date.available2007-01-03T04:21:02Z
dc.date.issued1998
dc.description.abstractThis paper is concerned with the structure of estimators of correlation matrices and correlation sequences. We argue that reasonable estimators of the correlation matrix are quadratic in the data and nonnegative definite. We also specify the structure of the estimator when the data are modulated: a property we call modulation covariance. We state a representation theorem for estimators that have these attributes. We also derive a representation for estimators that have the additional requirement that the estimated matrix be Toeplitz. These representation theorems admit estimators that use multiwindowed copies of the data. In many circumstances, this multiwindow structure is superior to the conventional sum of lagged-products or outer-product estimators.
dc.description.sponsorshipThis work was supported by the Office of Naval Research, Statistics and Probability Branch, under Contract N00014-89-J-1070.
dc.format.mediumborn digital
dc.format.mediumarticles
dc.identifier.bibliographicCitationMcWhorter, L. Todd and Louis L. Scharf, Multiwindow Estimators of Correlation, IEEE Transactions on Signal Processing 46, no. 2 (February 1998): 440-448.
dc.identifier.urihttp://hdl.handle.net/10217/745
dc.languageEnglish
dc.language.isoeng
dc.publisherColorado State University. Libraries
dc.relation.ispartofFaculty Publications
dc.rights©1998 IEEE.
dc.rightsCopyright and other restrictions may apply. User is responsible for compliance with all applicable laws. For information about copyright law, please see https://libguides.colostate.edu/copyright.
dc.subjectparameter estimation
dc.subjectmodulation
dc.subjectcorrelation methods
dc.subjectsequences
dc.subjectspectral analysis
dc.subject.lcshToeplitz matrices
dc.titleMultiwindow estimators of correlation
dc.typeText

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